Bridging the gap between Data Strategy and Execution using a Value-based approach
Most of us have seen the Gartner Analytics Ascendancy Model, which describes the goal of a data-driven analytics strategy to move from descriptive towards predictive and prescriptive analytics capabilities.
Business leaders and key decision-makers often face questions about whether their data strategies can support and execute the strategic business imperatives. But, unfortunately, the time spent and resources expended to collect, clean, and the process isn’t a walk in the park. As a result, we see key decision-makers reach a chasm between the outcomes they want and the data they have. Everyone wants to adopt a data-driven approach to problem-solving. Often the approach is to identify business problems and develop solutions that will solve them. Unfortunately, the needed data does not appear and needs to be deliberately collected from the various dynamic business systems we operate in. Given the disparate systems that exist, it is not easy to have all the data needed when the problem arises. A lot of companies implement data lakes, data ponds, data warehouses to support their cause. Often the names are misinterpreted and used interchangeably while they all support distinct outcomes. Businesses need to invest time to gather, clean and process the data.
But I’d like to begin with the question if the data is worth collecting? Businesses tend to collect data based on how easy it is to gather when starting the data-driven journey. While some data is easier to collect and process than others, there is still a considerable effort involved. So we should instead take a value-based approach to determine what data we should collect and process. This means assessing the net value of a data collection, processing exercise and the net effect it would have on the overall business or outcomes it would help achieve.
Businesses and Data teams need to build qualitative and quantitative arguments to get buy-in to shift towards a value-based data strategy. The path needs to be narrowed. Business and Data teams need a clear vision while defining and implementing tactical plans to get insights from data and analytics. The actions should be targeted, high-value use cases. By focusing on a specific outcome, you avoid the trap of wandering down aimlessly along a path that is too broad to yield any immediate value.
I’d love to hear about your data strategies and how you develop tactical plans to realise value.
